1. Field of the Invention
The present invention generally relates to a multiuser diversity technique, and more particularly to a user selection method in a zero-forcing beamforming algorithm for obtaining a multiuser diversity gain.
2. Description of the Related Art
Recently, a large amount of research is being conducted on a beamforming technique using multiple transmit and receive antennas for increasing spectrum efficiency and satisfying high-speed data transmission service requirements in wireless communication fields. Multiuser diversity refers to channel diversity between multiuser channels for improving a channel capacity using Rayleigh fading.
For multiuser diversity, transmission target users must be selected along with transmission times. In a wireless network environment, some users have the best channel state at a certain time. At this time, transmission is performed for associated users, such that the desired overall system capacity can be obtained. A water-filling algorithm optimizes the overall multiuser capacity by allocating the optimal power and transmission rate between subcarriers. However, the water-filling algorithm is not an optimal method in a common time/user space sharing the degree of time/space freedom in which users are already linked to a channel.
From an aspect of the maximization of a sum capacity, the simplest sharing method is to allocate all the power to a user with the largest degree of freedom. In this case, other users can perform communication after their channel states are improved. When the total transmission power is fixed in a Multiple-Input Multiple-Output (MIMO) channel, a base station can guarantee a high sum capacity, as compared with the case where an associated user with the best channel is selected and all the available capacity is allocated to the associated user, by simultaneously transmitting an independent data stream to multiple users.
Because receivers are unable to be cooperative in a downlink, successful transmission is determined according to whether a transmitter can simultaneously transmit independent signals while minimizing interference between users. If the transmitter knows interference information in a given channel considering additive noise and interference when a dirty-paper precoding algorithm, such as M. Costa, Writing On Dirty Paper, IEEE Trans. Inf. Theory IT—29, No. 3, 439—441, 1983, is exploited, it can obtain the same capacity as in an interference-free environment.
However, there are problems in that the dirty-paper precoding algorithm requires a new code with interference dependency and may not actually be implemented in the base station because the algorithm is complex. On the other hand, a zero-forcing algorithm is a suboptimal algorithm, but is a significantly simple approach for a capacity-related problem. In the zero-forcing algorithm, interference between all users is forced to 0.
The zero-forcing beamforming algorithm is known which can obtain the so-called optimal dirty-paper precoding algorithm and the asymptotic sum capacity when the number of users goes to infinity. However, there is a drawback in that the zero-forcing scheme exhibits better performance at a high Signal-to-Noise Ratio (SNR), but exhibits suboptimal performance at a low SNR.
On the other hand, a Dynamic Window Constrained Scheduling (DWCS) algorithm not only can overcome the drawback of the zero-forcing scheme, but also can obtain a high sum capacity, because the access distance is reduced and some users always become adjacent to one antenna or antenna cluster with a high SNR.
In the zero-forcing scheme, the number of antennas of a base station must be more than the total number of antennas of all receivers. When this condition is satisfied, active users with channels of quality based on requirements of the zero-forcing scheme are selected, such that the multiuser diversity gain can be obtained. Accordingly, the success or failure of the zero-forcing scheme depends on a process for selecting a user with the best channel quality at low complexity. Many user selection algorithms have been proposed for the zero-forcing scheme. However, the user selection algorithms consider a situation in which most of the user terminals have one antenna and the base station requires total Channel State Information (CSI). A need exists for a user selection method capable of minimizing complexity and improving performance at the time of considering user terminals with multiple receive antennas.